AI operations platform
Change one line.Measure every AI call.. See what each call costs.. Find your slowest model.. Catch every failure.
Observra is a gateway that sits between your applications and every AI provider. Point your existing SDK at it, and nothing else in your code changes.
observra gatewayrouting
base_url="https://gateway.observra.in/openai"
observationslatency / cost
- messages703ms$0.0044
- generateContent288ms$0.0006
- chat.completions412ms$0.0021
Routes to
- OpenAI
- Anthropic
- Gemini
- OpenRouter
- Ollama
The problem
Most teams get an AI invoice, not an explanation.
Applications call several providers, models, and agents at once. The basic operational questions stay unanswered until the bill arrives.
How much are we spending on AI right now, across every provider?
Which application or model is consuming the most tokens?
Why did requests suddenly get slower, and where?
Which requests failed, and what did they fail on?
How it works
One gateway. No rewrites.
The integration is a configuration change. What you get back is every call your applications make, priced and timed.
observra / production
p95 latency on gpt-4o rose 34% in the last hour. Every affected request came through one provider region.
p95 latency, mslast 60 min
01
Point your SDK at one base URL
Keep the OpenAI, Anthropic, or Gemini SDK you already use. The base URL and a gateway key change. Nothing else does.
02
Every request becomes an Observation
The gateway measures latency, tokens, cost, and outcome for each accepted request, then emits one immutable record. It happens asynchronously, so it never slows the call down.
03
Search, price, and govern from one stream
Those records drive request search, cost and token analytics, and provider comparisons. Alerts and budgets read the same stream.
Observation lifecycle
One event, six jobs.
Every accepted request produces exactly one immutable Observation. Everything downstream reads from it rather than re-measuring.
01
Ingest
Request enters the gateway, provider identified from the URL - no auto-detection.
02
Measure
Latency, token counts, and cost are computed against provider-aware pricing tables.
03
Emit
One immutable Observation event is written per accepted request - metadata-first by default.
04
Index
Observations are indexed for Request Explorer search, filters, and full-text lookup.
05
Aggregate
Rollups power dashboards: cost trends, token usage, provider and model comparisons.
06
Act
Insights surface anomalies today; alerts, budgets, and automation build on the same events.
Platform capabilities
One control surface for AI in production.
Each of these reads from the same Observation stream, so a number in a report and the same number in a request detail never disagree.
Metrics aggregation
Rollups into minute and hour buckets, with percentiles, so a month answers as fast as an hour.
Learn moreBaseline engine
Learns what normal looks like per application, so deviation is measured against history rather than a guessed number.
AI evaluation
Scoring for output quality rather than operational health, run off the event stream.
Anomaly detection
Latency, cost, token and error-rate deviations surfaced with the size of the gap.
Alert engine
Thresholds you set, evaluated on a loop, delivered with the values that tripped them.
Incident management
Alerts become incidents with an owner, a status, and a timeline of what happened.
Root cause analysis
Correlating anomalies, evaluations and the timeline to propose why something broke.
Policy engine
Thresholds and sensitivity scoped from the whole organization down to a single model.
DocsDashboards
Real-time and historical views of traffic, spend, alerts and incidents.
Why Observra
Four architectural commitments.
These are constraints the platform is built under, not positioning. Each one rules something out.
Your credentials never reach our storage
Provider API keys are forwarded, never stored and never logged. Your credentials, your billing relationship, and your data stay yours.
Provider-agnostic by design
Each provider gets a dedicated adapter: OpenAI, Anthropic, Gemini, Groq, Azure OpenAI, and more. Switching providers is a routing change, not a migration.
Customer traffic always wins
Analytics run asynchronously and off the request path. If the analytics pipeline degrades, your AI traffic keeps flowing.
Standards, not a proprietary format
W3C Trace Context for correlation, OpenTelemetry and OpenInference for execution graphs. Your telemetry stays portable.
Works with
Every provider, every framework, one standard.
Tested end to end across Node.js, Python, and Go. Streaming, tool calls, multi-agent workflows, and W3C trace propagation all verified through the gateway.
Providers
- OpenAI
- Anthropic
- Gemini
- GQGroq
- AZAzure OpenAI
- Ollama
- OpenRouter
Frameworks and agent SDKs
- LangChain
- LGLangGraph
- CrewAI
- LILlamaIndex
- SKSemantic Kernel
- MAMastra
- VCVercel AI SDK
- OAOpenAI Agents SDK
- GAGoogle ADK
- CGLangChainGo
- EIEino
- FGFirebase Genkit
- GLgo-llms
- IGInstructor-Go
Standards
- OpenTelemetry
- OIOpenInference
- MCMCP
- W3W3C Trace Context
Security and retention
Visibility without custody.
Observability should not cost you ownership of your data. These are enforced by the gateway's architecture, not settings you can misconfigure.
no key storageno asset storagemetadata first
No credential storage
Provider API keys are forwarded and never written down, at any point in the pipeline.
No asset storage
Files, images, audio, and video are never persisted by the gateway or the observability layer.
You control retention
You choose what is kept and for how long. The default is metadata only, so prompts and responses are opt in.
Metadata-first observability
Cost and performance data does not require capturing message content, so the useful default is also the private one.
Roadmap
From observability to AI operations.
Each phase depends on the one before it. We are honest about which is shipping and which is not.
01
Observe
In design partner testing
Gateway, requests, tokens, cost, latency, errors, and dashboards.
02
Detect
Next
Alerts, anomaly detection, and trend surfacing on the same Observation stream.
03
Control
Planned
Budgets, quotas, policies, and a kill switch for runaway spend or a misbehaving agent.
04
Optimize
Vision
Recommendations on model choice, prompt efficiency, and where cost is avoidable.
FAQ
Common questions
No. You keep using your existing provider SDKs - only the base URL and a Platform Gateway Key change. An optional helper SDK can simplify integration further, but it is never mandatory.
Limited cohort
Design partner program
Help shape the platform.
We are onboarding a small group of engineering teams already running AI in production. You get early access and direct input on what gets built next.